class_docstr: Resolves group-by items for potentially ambiguous inputs that are specified in queries / filters.
docstr: Returns the spec that corresponds the one described by spec_pattern and is valid for the query.
  
  For queries, if the pattern matches to a spec for the same element at different grains, the spec with the finest
  common grain is returned.
docstr_tok: ["Returns","the","spec","that","corresponds","the","one","described","by","spec_pattern","and","is","valid","for","the","query",".","For","queries",",","if","the","pattern","matches","to","a","spec","for","the","same","element","at","different","grains",",","the","spec","with","the","finest","common","grain","is","returned","."]
code: def resolve_matching_item_for_querying(
      self,
      spec_pattern: SpecPattern,
      suggestion_generator: Optional[QueryItemSuggestionGenerator],
  ) -> GroupByItemResolution:
      """Returns the spec that corresponds the one described by spec_pattern and is valid for the query.
  
      For queries, if the pattern matches to a spec for the same element at different grains, the spec with the finest
      common grain is returned.
      """
      push_down_visitor = _PushDownGroupByItemCandidatesVisitor(
          manifest_lookup=self._manifest_lookup,
          source_spec_patterns=(spec_pattern,),
          suggestion_generator=suggestion_generator,
      )
  
      push_down_result: PushDownResult = (
          self._resolution_dag.sink_node.accept(push_down_visitor)
      )
  
      if push_down_result.candidate_set.num_candidates == 0:
          return GroupByItemResolution(
              spec=None,
              issue_set=push_down_result.issue_set,
          )
  
      push_down_result = push_down_result.filter_candidates_by_pattern(
          BaseTimeGrainPattern(),
      )
      logger.info(
          f"Spec pattern:\n"
          f"{indent(mf_pformat(spec_pattern))}\n"
          f"was resolved to:\n"
          f"{indent(mf_pformat(push_down_result.candidate_set.specs))}"
      )
      if push_down_result.candidate_set.num_candidates > 1:
          return GroupByItemResolution(
              spec=None,
              issue_set=push_down_result.issue_set.add_issue(
                  AmbiguousGroupByItemIssue.from_parameters(
                      candidate_set=push_down_result.candidate_set,
                      query_resolution_path=MetricFlowQueryResolutionPath.from_path_item(
                          self._resolution_dag.sink_node
                      ),
                  )
              ),
          )
  
      return GroupByItemResolution(
          spec=push_down_result.candidate_set.specs[0],
          issue_set=push_down_result.issue_set,
      )
  
imports: from __future__ import annotations
  import logging
  from dataclasses import dataclass
  from typing import Optional, Tuple
  from dbt_semantic_interfaces.call_parameter_sets import TimeDimensionCallParameterSet
  from dbt_semantic_interfaces.naming.keywords import METRIC_TIME_ELEMENT_NAME
  from dbt_semantic_interfaces.references import TimeDimensionReference
  from dbt_semantic_interfaces.type_enums import TimeGranularity
  from metricflow.mf_logging.formatting import indent
  from metricflow.mf_logging.pretty_print import mf_pformat
  from metricflow.model.semantic_manifest_lookup import SemanticManifestLookup
  from metricflow.naming.object_builder_scheme import ObjectBuilderNamingScheme
  from metricflow.query.group_by_item.candidate_push_down.push_down_visitor import PushDownResult, _PushDownGroupByItemCandidatesVisitor
  from metricflow.query.group_by_item.resolution_dag.dag import GroupByItemResolutionDag, ResolutionDagSinkNode
  from metricflow.query.group_by_item.resolution_path import MetricFlowQueryResolutionPath
  from metricflow.query.issues.group_by_item_resolver.ambiguous_group_by_item import AmbiguousGroupByItemIssue
  from metricflow.query.issues.issues_base import MetricFlowQueryResolutionIssueSet
  from metricflow.query.suggestion_generator import QueryItemSuggestionGenerator
  from metricflow.specs.patterns.base_time_grain import BaseTimeGrainPattern
  from metricflow.specs.patterns.spec_pattern import SpecPattern
  from metricflow.specs.patterns.typed_patterns import TimeDimensionPattern
  from metricflow.specs.specs import LinkableInstanceSpec, LinkableSpecSet
label_desc: Use image node_id 2 for calling the GroupByItemResolver obj's underlying member method code with example usage: obj.resolve_matching_item_for_querying(spec_pattern, suggestion_generator) and returns: GroupByItemResolution, GroupByItemResolution, GroupByItemResolution